Analyze with Smarter Job Titles

We’re excited to roll out Titles 2.0, a significant step forward in your ability to analyze global labor market data. Now available in Global Talent Analyst, this new feature brings together our patent-pending machine translation and title-level intelligence to help you search, sort, and analyze job titles across markets with unprecedented precision.

You might be thinking, "Didn’t we already translate job titles before?"

Yes—but not like this. Until now, our Lightcast Occupation Taxonomy (LOT) system has focused on mapping accurate global jobs to occupations and standard codes. But it meant you couldn’t always drill down into the actual job titles you care about—especially in English. Titles were translated behind the scenes for APIs and LOT, but weren’t searchable in Analyst itself.

With Titles 2.0:

• You can input job titles directly—in English—and search across international datasets.

• Titles are cleaned, clustered, and normalized using the same title intelligence trusted in our U.S. data.

• You’ll see title-level suggestions and mappings based on real-world usage, not just SOC or occupation-level summaries. This update gives you a more granular, role-specific lens—perfect for organizations that rely on precise job titles (e.g., “Computer Programmer vs. Computer Programmer Analyst”).

• Your organization will have a direct, intuitive window into the power of the LOT.

So whether you’re comparing global hiring trends, analyzing title variants, or exploring how roles show up in different countries, Titles 2.0 gives you the lowest layer of signal—where the nuance lives.

This new functionality is now live in Global Talent Analyst, APIs, and Data Shares, including Snowflake.